Dynamic range setting for vehicular radars

ABSTRACT

A vehicle control system includes a set of radars, with each radar of the set including a depth setting which controls a corresponding range of the radar. The corresponding range of at least one radar may be adjusted based on contextual information, as determined by the vehicle when the vehicle is in use.

RELATED APPLICATIONS

This application claims benefit of priority to Provisional U.S. PatentApplication No. 62/304,131, filed Mar. 4, 2016; the aforementionedpriority application being hereby incorporated by reference in itsentirety.

BACKGROUND

Vehicles currently employ radar as a sensor for enabling proximity andcollision detection. As general rules, to increase maximum

detection range (R), automotive radar needs a larger signal to noiseratio (SNR). To increase SNR, radar can increase illumination time ordecrease the field of view required to illuminate. Under manyconventional approaches, vehicles generally use radars with static rangesettings.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A illustrates an example of a radar system for a vehicle.

FIG. 1B illustrates an example of a control system for a vehicle thathas autonomous capability.

FIG. 2 illustrates an example method for operating a vehicle todetermine a depth range of one or more radars on the vehicle.

FIG. 3 illustrates an example vehicle equipped with a radar system thatdynamically configures individual radars of the vehicle to have varyingdepth ranges.

FIG. 4 is a block diagram that illustrates a control system for avehicle upon which embodiments described herein may be implemented.

DETAILED DESCRIPTION

Examples provide for a vehicle with radar that is dynamicallyconfigurable for operational depth range. More specifically, a vehiclemay include a set of radars, with each radar of the set including adepth setting which controls a corresponding range of the radar when itis in use on the vehicle. The vehicle may determined, or otherwiseobtain contextual information from any one of multiple possible sourcesas the vehicle progresses over a road segment. A vehicle control systemmay adjust the corresponding range of at least one radar based on thecontextual information.

One or more embodiments described herein provide that methods,techniques, and actions performed by a computing device are performedprogrammatically, or as a computer-implemented method. Programmatically,as used herein, means through the use of code or computer-executableinstructions. These instructions can be stored in one or more memoryresources of the computing device. A programmatically performed step mayor may not be automatic.

One or more embodiments described herein can be implemented usingprogrammatic modules, engines, or components. A programmatic module,engine, or component can include a program, a sub-routine, a portion ofa program, or a software component or a hardware component capable ofperforming one or more stated tasks or functions. As used herein, amodule or component can exist on a hardware component independently ofother modules or components. Alternatively, a module or component can bea shared element or process of other modules, programs or machines.

Numerous examples are referenced herein in context of an autonomousvehicle. An autonomous vehicle refers to any vehicle which is operatedin a state of automation with respect to at least one of steering,propulsion or braking. Different levels of autonomy may exist withrespect to autonomous vehicles. For example, some vehicles today enableautomation in limited scenarios, such as on highways, provided thatdrivers are present in the vehicle. More advanced autonomous vehiclesdrive without any human driver inside the vehicle. Such vehicles oftenare required to make advance determinations regarding how the vehicle ismaneuver given challenging surroundings of the vehicle environment.

FIG. 1A illustrates an example of a radar control system for a vehicle.In an example of FIG. 1A, a vehicle 12 can be either autonomous ornon-autonomous, and can include a radar system 10 that includes radarcontrol logic 18 for controlling a set of radars 22. The radar system 10can be provided for a variety of uses, depending on design andimplementation. In an example, the radar system 10 interfaces with oneor more components 20 of the vehicle 12 in order to perform functionssuch as signal driver alerts as to possible hazards or dangers. Invariations such as described with FIG. 1B, the radar system 10 can beintegrated with a fully or partially autonomous vehicle. In the contextof such vehicles, the radar system 10 can be used to implement evasiveactions, generate external alerts, monitor approaching roadways, andperform other functions.

The set of radars 22 for the radar system 10 may be distributed atpre-selected locations of the vehicle 12. Each of the radars 22 caninclude a radar transmitter/receiver, from which an outward radar signalis generated and then subsequently detected on reflection when an objectis encountered (e.g., by way of a radar scan). In some examples, each ofthe individual radars 22 can have a respective orientation (e.g.,represented by a viewing angle 17), which can be adjusted about anazimuth (shown by Z axis in FIG. 1A, coming out of the page), while thevehicle 12 moves on the roadway (e.g., along the Y-axis). To further anexample of FIG. 1, individual radars 22 present on the vehicle can havetheir respective viewing angle adjusted between 22.5 and 90 degrees,depending on the intended design or capability of the radar 22. Ingeneral, the radars 22 can each operate at one of multiple possibleangular orientations within an angular range of viewing angles. At eachof the orientations, individual radars 22 of the radar system 10 canoperate to generate outwardly directed radar signals, and further todetect incoming signals which result from reflections of the outwardlyreflected signals. Under some examples, the radar control logic 18 caninclude discrete or radar-specific control elements which controlprogression of radar scans from the particular radar at discreteorientations of the respective angular range.

Additionally, examples recognize that a depth range setting 24 ofindividual radars 22 can be controlled by a duration in which a givenradar 22 is generating radar signals from a particular orientation. Moregenerally, the depth range setting 24 of individual radars 22 can be setby parameters of time (e.g., duration) and energy expended in generatingoutward radar signals at a particular moment (e.g., when the radar 22 isoperated for continuous duration at a given orientation). Thus, radars22 can be operated for different depth ranges based on the overallenergy expended in generating the outward radar signal. Moreover, whenindividual radars 22 are operated for close range detection, the radar22 can be moved between orientations of the angular range more quickly,thus providing a better coverage for detecting nearby (or large)objects.

Some conventional approaches dedicate specific radars for long range useand others for short range use, recognizing the benefit of detectingboth far and close objects alike. However, such conventional approaches,in which radars 22 are assigned to designations of short or long range,fail to accommodate numerous use cases which vehicles encounter on dailybasis, such as, for example, when vehicles approach an intersection ortravel on a road that is merging with another road. In contrast,examples provide for radar control logic 18 to selectively determine thedepth range setting 24 of one or more of the radars 22 on the vehicle12, based at least in part on contextual information, and morespecifically, by location data 23 and geographic information 25. Oncedetermined, the radar control logic 18 can signal the depth rangesetting 24 to the respective radars 22. In determining the depth rangesetting 24, the geographic information 25 can include, for example,information about road segments on which the vehicle is driving on, oris expected to drive on, as the vehicle progresses on a route. Thelocation data 23 can be obtained from, for example, a GPS receiver 32resident in the vehicle 12, or a mobile computing device carried withinthe vehicle by a driver or passenger.

According to some examples, the vehicle 12 includes a computer systemand human interface for implementing a navigation system 34 utilizing amap database 27. The map database 27 can be local or remote to thevehicle 12. The navigation system 34 can identify geographic information25 from the map database 27 for use by radar control logic 18. The radarcontrol logic 18 can determine, among other functions, the range depthsetting 18 of individual radars 22 based on a specific road segment onwhich the vehicle 12 travels on, and/or a specific road segment whichthe vehicle 12 is approaching and will travel on. In some examples, theradar control logic 18 can implement a set of rules from which the depthrange setting 24 of individual radars 22 can be determined.

As an addition or variation, the radar control logic 18 can specify thedepth range setting 24 of a particular radar 22 at a given angularorientation or subset of angular orientations, separate from alternativedepth ranges for other orientations of the same radar 22. For example,one of the radars 22 may be capable of an angular rotation of up to 90°,and the depth range for the particular radar 22 may be set to a maximumfor the angular orientation that varies between 0° and 10°, while thedepth range of the radar can be minimized at the other angularorientations of the radar. Thus, in instances when the radar performsseveral scans at different angular orientations, the depth range of theradar 22 may be controlled between a maximum and minimum depth range. Insuch cases, the progression of the radar 22 through the differentangular orientations may vary by duration of time, with thoseorientations in which longer scans are performed requiring a greateramount of time.

The radar control logic 18 can be implemented in a variety of forms,using hardware, firmware, and/or software. In one example, the radarcontrol logic 18 implements rules based on the road segment that thevehicle 12 approaches or travels on. For example, when the vehicle 12travels forward on a given road, the default radar depth range settings24 may specify that a forward-looking radar 22 has a maximum depth rangesetting 24, and other peripheral or laterally positioned radars 22 havea minimum or intermediate depth range setting 24. When the vehicle 12approaches a merge lane, the radar control logic 18 can implement a rulethat maximizes the depth range setting 24 of peripherally positionedradars 22 so as to enable a greater view of traffic or objects in theapproaching merging lane. As another example, the radar control logic 18implements alternative rules for approaching intersections, where, forexample, peripherally positioned radars 22 have their depth rangesetting 24 maximized to detect approaching traffic in either direction.As still another variation, radar control logic 18 can implement a ruleto generate a radar cone that can encompass the depth of an approachingcross-walk, without encroaching on the intersection where cross-trafficmay exist. In such an example, the depth range setting of the frontfacing radar 22 can be maximized to capture the full crosswalk, and thedepth range setting 24 can be reduced incrementally as the vehicleapproaches the intersection, so that the cross traffic of theintersection does not generate false radar alerts.

According to some examples, the vehicle component 20 receives radarinput 21 from the radars 22. The radar input 21 can be processed, eitherdirectly (e.g., as raw data) or indirectly (e.g., processed, commands insemantic form, etc.) from the radars 22 or the radar interfaces. Forexample, additional logic may translate the radar input 21 from either asingle radar source, or from a group of the radars 22, into a specificsemantic label which identifies an action, command or input parameter.In one example, radar input 21 can be interpreted to detect potentialhazards which can impede the vehicles path or cause a collision from aparticular direction surrounding. The vehicle component 20 whichreceives the radar input 21 can correspond to a human interfacecomponent that can generate an audible or visual alert of the potentialcollision or hazard. In variations such as described with FIG. 1B, theradar input 21 can be used for other actions or operations, such ascontrolling specific autonomous operations of the vehicle. For example,if the radar input 21 indicates a hazard, the vehicle component 20 canimplement an evasive action, such as braking, while concurrentlygenerating alarm. Accordingly, in some variations, the radar input 21can be received by a vehicle component that corresponds to a controlsystem, or component thereof, for an autonomous vehicle.

The nature of radar input 21 can increase with complexity when used withautonomous vehicles. For example, in an autonomous vehicle environment,the radar input 21 can scan traffic in the direction of travel, and thenselect the lane for the vehicle based on the perceived traffic.Likewise, radar control logic 18 may set peripheral radars of thevehicle to a maximum when performing right turns, or turns into one-waytraffic, so as to detect vehicles which a driver or camera may miss.

While an example of FIG. 1A is described in context of functionalityprovided with a vehicle, variations provide for other device platformsto implement some or all of the steps for dynamically determining thedepth range of individual radars 22. In particular, variations providefor functionality to select and set the depth range of individual radars22 to be implemented by a mobile computing device carried within thevehicle 12, and/or a network service which communicates with the vehicleand/or the mobile computing device. For example, the radar system 10 caninclude a programmatic interface 15 which is accessible by anapplication executing on the mobile computing device and/or networkservice in order to provide depth range settings 24 for individualradars 22 of the radar system 10. In one implementation, the mobilecomputing device executes a navigation application, and the radar system10 can interface or execute as part of the navigation application tocontrol the depth range setting 24 of the individual radars 22.

FIG. 1B illustrates an example of a control system for a vehicle thathas autonomous capability. In an example of FIG. 1B, a control system100 is used to autonomously control at least some aspects of the vehicle80 in a given geographic region. By way of example, the vehicle 80 withautonomous capability can correspond to a human-driven vehicle, havingautonomous features for controlling the vehicle for purpose of providingan emergency response to a detected hazard, for other safety relatedpurposes (e.g., incapacitated driver), or at the preference of thedriver. In such examples, the level of autonomous control for thevehicle can vary. For example, the autonomous control can be limited to:a specific action (e.g., hard brake), in-lane vehicle adjustments (e.g.,accelerating or braking in a given lane), multi-lane autonomous drivingwithout route execution capability (e.g., in-lane adjustments, lanechanging), or complete route execution capability. In variations, thevehicle 80 can be autonomous, meaning no human driver may be resident inthe vehicle. In examples described, an autonomously driven vehicle canoperate without human control. For example, in the context ofautomobiles, an autonomously driven vehicle can steer, accelerate,shift, brake and operate lighting components. Some variations alsorecognize that an autonomous-capable vehicle can be operated eitherautonomously or manually, depending on mode selection.

Accordingly, depending on the capability of the vehicle 80, the controlsystem 100 can operate to process input from a variety of sources, aswell as to selectively control one or more facets of the vehicle as thevehicle travels over road segments. The control system 100 can includenumerous sensor interfaces for processing sensor input from, forexample, a set of radars, as well as other sensors such as cameras(e.g., stereoscopic cameras, short/long range cameras, LiDar, etc.), andsonar. The control system 100 can utilize specific sensor resources inorder to intelligently operate the vehicle 80 in most common drivingsituations. For example, the control system 100 can operate the vehicle80 by autonomously steering, accelerating and/or braking the vehicle 80as the vehicle progresses to a destination. The control system 100 canperform vehicle control actions (e.g., braking, steering, accelerating)and route planning using sensor information, as well as other inputs(e.g., transmissions from remote or local human operators, networkcommunication from other vehicles, etc.). Still further, in someexamples, the vehicle 80 includes one or more interfaces which detecthuman input, either made directly through the control system 100 orthrough control features of the vehicle (e.g., steering wheel, gaspedal, etc.).

In an example of FIG. 1B, the control system 100 includes a computer orprocessing system which operates to process sensor data that is obtainedon the vehicle with respect to a road segment that the vehicle is aboutto drive on. The sensor data can be used to determine actions which areto be performed by the vehicle 80 in order for the vehicle to continueon a route to a destination. In some variations, the control system 100can include other functionality, including a GPS receiver 138 and awireless receiver 139. The wireless receiver 138 can be used to sendand/or receive wireless communications with one or more remote sources.In controlling the vehicle, the control system 100 can issueinstructions and data, shown as commands 85, which programmaticallycontrols various electromechanical interfaces of the vehicle 80. Thecommands 85 can serve to control some or all of the operational aspectsof the vehicle 80, including propulsion, braking, steering, andauxiliary behavior (e.g., turning lights on). With respect to a specificexample of FIG. 1B, the autonomous vehicle 80 can be equipped with oneor more types of sensors 101, 103, 105, which combine to provide acomputerized perception of the space and environment surrounding thevehicle 80. Likewise, the control system 100 can operate within theautonomous vehicle 80 to receive sensor data from the collection ofsensors 101, 103, 105, and to control various electromechanicalinterfaces for operating the vehicle on roadways.

In more detail, the sensors 101, 103, 105 operate to collectively obtaina sensor view of the area surrounding the vehicle 80 (e.g., 360-degreeview). By way of example, the sensors 101, 103, 105 enable the vehicle80 to obtain information about what is near the sides and/or rear of thevehicle, as well as what is both near and far from the front of thevehicle 80 as the vehicle travels. By way of example, the sensors 101,103, 105 include multiple sets of cameras sensors 101 (video camera,stereoscopic pairs of cameras or depth perception cameras, long rangecameras), radar 103, sonar and/or LiDar sensors.

Each of the sensors 101, 103, 105 can communicate with, or utilize acorresponding sensor interface 110, 112, 114. Each of the sensorinterfaces 110, 112, 114 can include, for example, hardware and/or otherlogical component which is coupled or otherwise provided with therespective sensor. For example, the sensors 101 can include a videocamera and/or stereoscopic camera set which continually generates imagedata of an environment of the vehicle 80. The sensor interface 110 mayinclude a dedicated processing resource, such as provided with a fieldprogrammable gate array (“FPGA”) which receives and/or processes rawimage data from the camera sensor. Likewise, radars 103 can provide anadditional or alternative sensor set. As described with other examples,the radars 103 can be dynamically configurable to determine theirrespective depth setting based on contextual information determined fromthe vehicle in motion. The radar interface 112 can reside or operatewith individual radars 103, and/or provide a centralized controller formultiple radars 103 connected by a data bus. The interfaces 110, 112,114 can pre-process the raw sensor data and/or perform more complexprocessing. With respect to radars 103, the interface(s) 112 can receivethe depth settings and implement the configurations on the correspondingradars 103.

According to one implementation, the vehicle interface subsystem 90 caninclude or control multiple interfaces to control mechanisms of thevehicle 80. By way of example, the vehicle interface subsystem 90 caninclude a propulsion interface 92 to electrically (or throughprogramming) control a propulsion component (e.g., a gas pedal), asteering interface 94 for a steering mechanism, a braking interface 96for a braking component, and lighting/auxiliary interface 98 forexterior lights of the vehicle. The vehicle interface subsystem 90and/or control system 100 can include one or more controllers 84 whichreceive one or more commands 85 from the control system 100. Thecommands 85 can include route information 87 and one or more operationalparameters 89 which specify an operational state of the vehicle (e.g.,desired speed and pose, acceleration, etc.).

The controller(s) 84 generate control signals 119 in response toreceiving the commands 85 for one or more of the vehicle interfaces 92,94, 96, 98. The controllers 84 use the commands 85 as input to controlpropulsion, steering, braking and/or other vehicle behavior while theautonomous vehicle 80 follows a route. Thus, while the vehicle 80 mayfollow a route, the controller(s) 84 can continuously adjust and alterthe movement of the vehicle in response receiving a corresponding set ofcommands 85 from the control system 100. Absent events or conditionswhich affect the confidence of the vehicle in safely progressing on theroute, the control system 100 can generate additional commands 85 fromwhich the controller(s) 84 can generate various vehicle control signals119 for the different interfaces of the vehicle interface subsystem 90.

According to examples, the commands 85 can specify actions that are tobe performed by the vehicle 80. The actions can correlate to one ormultiple vehicle control mechanisms (e.g., steering mechanism, brakes,etc.). The commands 85 can specify the actions, along with attributessuch as magnitude, duration, directionality or other operationalcharacteristic of the vehicle 80. By way of example, the commands 85generated from the control system 100 can specify a relative location ofa road segment which the autonomous vehicle 80 is to occupy while inmotion (e.g., change lanes, move to center divider or towards shoulder,turn vehicle etc.). As other examples, the commands 85 can specify aspeed, a change in acceleration (or deceleration) from braking oraccelerating, a turning action, or a state change of exterior lightingor other components. The controllers 84 translate the commands 85 intocontrol signals 119 for a corresponding interface of the vehicleinterface subsystem 90. The control signals 119 can take the form ofelectrical signals which correlate to the specified vehicle action byvirtue of electrical characteristics that have attributes for magnitude,duration, frequency or pulse, or other electrical characteristics.

According to some examples, the vehicle 80 includes multiple radars 103,and the control system 100 includes a radar control logic 160 to controland utilize the radars 103 of the vehicle 80. The multiple radars 103can be distributed on the vehicle 80 in accordance with a predeterminedconfiguration. For example, a set of four or six radars 103 can bepositioned at various locations of the vehicle in order to providecapability for 360-degree radar visibility. The control system 100 caninclude functionality that determines dynamically, based on context, thedepth range of at least some of the radars 22.

In an example of FIG. 1B, the control system 100 includes an eventdetermination logic 120, routing engine 122, localization component 126and vehicle control interface 128. The event determination logic 120 andthe routing engine 122 combine to generate inputs which the vehiclecontrol interface 128 maps into commands 85 for controlling theoperation of the vehicle 80. In an example in which the vehicle 80 isautonomous, the routing engine 122 may receive, for example, adestination input from a user or external source. The routing engine 122may also receive GPS data 135 from a GPS receiver 138. The routingengine 122 may then interface with a map store 125 to determine theroute 161 for the vehicle 80, which can then be signaled to the vehiclecontrol interface 128. In turn, the vehicle control interface 128 mayexecute turns, brakes, accelerations and other actions to implement theselected route.

The control system 100 can include a data store 118 which maintains thevarious types of incoming sensor data, for use with the various logicalcomponents of the control system 100. The data store 118 can be providedwith logic that structures and normalizes incoming data from differentsources, so that the incoming data has a common format and structure.Additionally, synchronization logic 136 can be provided with the controlsystem 100 to enable data packets, representing sensor values measuredat the various sensors 101, 103, 105 to be synchronized in accordancewith a common clock signal 137. For example, control system 100 mayutilize the clock signal 137 from GPS receiver 138 in order to generatethe reference clock signal 137 for synchronizing sensor data 111 fromthe various sensor data sources.

According to some examples, the event determination logic 120 processesuses synchronized sensor data from the data store 118 to detect routedisruptions, potential hazards or obstructions, and other events. Theevent determination logic 120 may thus illustrate a simplifiedrepresentation of one or multiple models or logical entities which canprocess the sensor inputs in order to perceive information about eventswhich that will or will likely interfere with the vehicle's progress orsafety. By way of example, the event determination logic 120 processesone or multiple types of image input, radar input, and/or sonar input inorder to generate event input 121 for the vehicle control interface 128.The event input 121 can, for example, signal the vehicle controlinterface 128 to generate commands 85 which cause the vehicle 80 toperform any one or more of: (i) progress without change, (ii) slow down,(iii) brake suddenly, (iv) swerve or take evasive action, or (v) performalternative actions (e.g., lane signaling, sounding horn, etc.). Theevent determination logic 120 can generate the event input 121 inresponse to, for example, detecting (i) another object in the path ofthe vehicle, (ii) detecting traffic signals, (iii) detecting roadsegments (e.g., intersections) and/or various other objects. Separatemodels may be used for detecting objects of different types, usingsensor data 111 of different kinds. For example, the event determinationlogic 120 may use sensor input 111 from a combination of radar 103 andone or more types of images in order to spot hazards in a current orprojected path of the vehicle 80. Will

The localization component 126 can use sensor data from the data store118 in order to determine the precise location (e.g., within a foot, 3-4inches, etc.) and pose of the vehicle at a given road segment. Thus, thelocalization component 126 can detect a specific lane the vehicle istraveling in, whether the vehicle is in the middle of a lane change,and/or an orientation of the vehicle with respect to the road segment.

Components such as event determination 120 and localization 126 canutilize multiple types of sensor data 111. For example, the eventdetermination logic 120 can use image data, including three dimensionalor stereoscopic images captured of a scene surrounding or in front ofthe vehicle, LiDar images, and/or video, for purpose of detecting apossible obstruction, and determining what action should be taken by thevehicle (if any) based on the classification and relative location ofthe object. In such context, the event determination logic 120 canutilize radar as an early detection system for focusing one or morecameras of the vehicle 80. When radar input detects a potentialobstruction, the event determination logic 120 can signal the vehiclecontrol interface 128 to slow down initially (e.g., command to stopaccelerating and or light braking), thus providing the image recognitionprocesses more time to identify the potential obstruction. The vehiclecontrol interface 128 can then determine the action that is to beperformed to avoid collision based on or more defined image processing.

Likewise, the locality determination component 126 can use image datasuch as provided by LiDar and/or stereoscopic cameras, in order toobtain, for example, image pointlets which can identify the pose andlocation of the vehicle 80 on a particular road segment. With highlyprecise location determination, the vehicle 80 can better understand itssurroundings, including identifying those objects which are not static(e.g., landmarks, permanently fixed objects such as buildings andmailboxes). Moreover, with highly precise positioning and pose, thevehicle 80 can utilize map data 129 which carries multiple layers ofadditional contextual information, separate from the road networkdescription provided by conventional maps. In one example, the controlsystem 100 stores a map store 125, comprising map data 129 whichidentifies specific characteristics of the road segment on which thevehicle 80 is traveling. Additionally, the map store 125 can identifystatic objects, such as landmarks, signages, buildings of thesurroundings, and other objects.

While examples provided with FIG. 1B illustrate numerous facets of thevehicle 80 which can be controlled via the control system 100,variations to examples described can provide for human driven vehicles,or hybrid combinations, in which the control system 100 has more limitedability to control the operation of the vehicle 80.

According to some examples, the control system 100 includes radarcontrol logic 160 and context determination component 162. The contextdetermination component 162 can parse sensor data, output of logicalcomponents, and/or various other datasets in order to determinecontextual parameters 163. The contextual parameters 163 can identify,for a given interval of time, a radar range for different points of anoverall radar view which is available for the vehicle, given physicalpositioning and orientation of individual radars 103 on the vehicle 80.For example, for cases where the radars 103 combined to provide a 360°radar view of the vehicle, the contextual parameters 163 can specifyspecific death ranges at angular increments of the total radar view.

The radar control logic 160 can utilize the contextual parameters 163 inorder to dynamically configure the radars 103 of the vehicle 80.Specifically, the radar control logic 160 can identify the depth rangesetting 165 for each radar 103 of the vehicle. In variations, the radarcontrol logic 160 can also specify the time interval 167 for when thespecified depth ranges are to be in place. In variations, the radarcontrol logic 160 can sub-configure individual radars 103 to havedifferent depth ranges when the individual radars 103 are at a givenorientation in their respective angular range of operation.

According to some examples, the context determination component 162determines contextual information in the form of map data 129identifying an upcoming road segment on which the vehicle 80 is totraverse. As shown with an example of FIG. 3, the map data 129 canidentify road network conditions such as a merging lane. The contextdetermination component 162 can determine from the map data 129,contextual parameters 163 in the form which include depth range atdifferent available viewing angles of the radars 103. Thus, for example,the depth range of radars 103 which are oriented in the direction of amerging lane can be increased to view potential hazards or objects in amerging lane. The contextual parameters 163 can also include a timeinterval, corresponding to when the vehicle will need to view thelong-range radar information. Thus, the time interval can correspond toa duration that initiates at some point in the future (e.g., 1-2 secondin the future). In this way, the map data 129 enables planningoperations to optimize the functioning of the radars 103, as theimmediate path of the vehicle 80 is determined from the known route forthe given trip and the road segment of the vehicle's travel, as providedfrom the map store 125.

In other variations, context determination component 162 can receivecontextual information from logical components such as localization 126and/or event determination logic 120. The localization component 126can, for example, enable a more granular use of map data 129, such as toidentify, for example, driveways that can hide approaching vehicles, orareas in the upcoming road segment which are occluded but possibleinlets of obstruction for cars, pedestrians, bicycles or other objects.The event determination logic 120 can also provide contextualinformation in the form of a detected (and potential) interference orhazard. For example, the event determination logic 120 can identify apotentially stalled vehicle in a given lane adjacent to that which thevehicle is using, and the context determination component 162 can parsethe event input 121 or alert for purpose of utilizing long-range radarto identify the relative direction of the detected hazard. Thelong-range radar may then enable the control system 100 to betterunderstand the potential safety risk of the stalled vehicle (e.g., suchas whether a person is near the stalled vehicle). In each of theexamples provided, the context determination logic 162 can determinecontextual parameters 163 which identify a desired depth range for thevehicles radar 103 at a particular angle or orientation.

Among other benefits, examples as described enable the radars 103 to bemaintained at a default setting, such as at a low-power setting whichenable proximity detection, while selectively using long-range radarcapabilities based on detected contextual information (e.g., upcomingroad segment, potential hazard or obstruction, hidden driveway, etc.).The selective and dynamic configuration of radars 103 for long-rangedetection can save power, while optimizing the detectability provided bythe radars 103 for need.

FIG. 2 illustrates an example method for operating a vehicle todetermine a depth range of one or more radars on the vehicle. An examplesuch as provided by FIG. 2 may be implemented by vehicles and/or controlsystem such as described with examples of FIG. 1A and FIG. 1B.Accordingly, reference may be made to elements or components describedwith other figures for purpose of illustrating a suitable component forperforming a step or sub-step being described.

With reference to FIG. 2, a vehicle may be operated with a set of radars(210). Each radar in the set can include a depth setting which controlsa corresponding range of the radar. Depending on variations andimplementation, the vehicle can be human driven, autonomous and withouthuman driver, or partially autonomous.

Contextual information can be determined about a trip of the vehicle asthe vehicle progresses over a given road segment (220). By way ofexample, the contextual information can include identification ofspecific types of road segments (e.g., merge lanes, intersections,crosswalks, hidden driveways, etc.). To contextual information can bedetermined from map data, such as provided on vehicles for purpose ofnavigation, or as used in some autonomous vehicles for localizationdetermination and other functions. In variations, the contextualinformation can reflect autonomous identification of potential objectsof obstruction or hazard, such as determined from analyzing image and/orradar sensor data. Still further, contextual information can reflect theamount of traffic that is present on the road the vehicle is travelingon, as well as the time of day, the day of week or calendar day, theweather, and various other types of information.

Based on the contextual information, the vehicle (or vehicle controlsystem) can adjust the corresponding range of one or more radars on thevehicle (230). For example, at least one radar may capture a long-rangeradar view of a relevant road segment for the vehicle. As described withother examples, the long-range radar can provide purpose such as earlydetection of road hazards.

FIG. 3 illustrates an example vehicle equipped with a radar controlsystem that dynamically configures individual radars of the vehicle tohave varying depth ranges. The vehicle 310 can travel on the roadsegment 302, and use map information (e.g., for navigational purposes)to detect an upcoming merge lane 304. In anticipation of the merge lane,the vehicle 310 can change the depth range of one or multiple radars onthe passenger side of the vehicle to better detect potential vehicles orother objects which can potentially collide with the vehicle when thelane merger occurs. As described with other examples, parameters forconfiguring individual radars can specify, for example, the angle ofcoverage, and/or the desired depth. In some variations, the parameterscan also specify an interval of time (e.g., start time, duration, endtime) when the increase in the radar depth range is to be made present.

Hardware Diagrams

FIG. 4 is a block diagram that illustrates a control system for avehicle upon which embodiments described herein may be implemented. Avehicle control system 400 can be implemented using a set of processors404, memory resources 406, multiple sensors interfaces 422, 428 (orinterfaces for sensors) and location-aware hardware such as shown by GPS424.

According to some examples, the control system 400 may be implementedwithin a vehicle with software and hardware resources such as describedwith examples of FIG. 1A, FIG. 1B and FIG. 2. In an example shown, thecontrol system 400 can be distributed spatially into various regions ofa vehicle. For example, a processor bank 404 with accompanying memoryresources 406 can be provided in a vehicle trunk. The various processingresources of the control system 400 can also include distributed sensorprocessing components 434, which can be implemented usingmicroprocessors or integrated circuits. In some examples, thedistributed sensor logic 434 can be implemented using field-programmablegate arrays (FPGA).

In an example of FIG. 4, the control system 400 further includesmultiple communication interfaces, including one or more multiplereal-time communication interface 418 and asynchronous communicationinterface 438. The various communication interfaces 418, 438 can sendand receive communications to other vehicles, central services, humanassistance operators, or other remote entities for a variety ofpurposes. In the context of FIG. 1A and FIG. 1B, control system 100 canbe implemented using the vehicle control system 400, such as shown withan example of FIG. 4. In one implementation, the real-time communicationinterface 418 can be optimized to communicate information instantly, inreal-time to remote entities (e.g., human assistance operators).Accordingly, the real-time communication interface 418 can includehardware to enable multiple communication links, as well as logic toenable priority selection.

The vehicle control system 400 can also include a local communicationinterface 426 (or series of local links) to vehicle interfaces and otherresources of the vehicle. In one implementation, the local communicationinterface 426 provides a data bus or other local link toelectro-mechanical interfaces of the vehicle, such as used to operatesteering, acceleration and braking, as well as to data resources of thevehicle (e.g., vehicle processor, OBD memory, etc.).

The memory resources 406 can include, for example, main memory, aread-only memory (ROM), storage device, and cache resources. The mainmemory of memory resources 406 can include random access memory (RAM) orother dynamic storage device, for storing information and instructionswhich are executable by the processors 404.

The processors 404 can execute instructions for processing informationstored with the main memory of the memory resources 406. The main memorycan also store temporary variables or other intermediate informationwhich can be used during execution of instructions by one or more of theprocessors 404. The memory resources 406 can also include ROM or otherstatic storage device for storing static information and instructionsfor one or more of the processors 404. The memory resources 406 can alsoinclude other forms of memory devices and components, such as a magneticdisk or optical disk, for purpose of storing information andinstructions for use by one or more of the processors 404.

One or more of the communication interfaces 418 can enable theautonomous vehicle to communicate with one or more networks (e.g.,cellular network) through use of a network link 419, which can bewireless or wired. The control system 400 can establish and use multiplenetwork links 419 at the same time. Using the network link 419, thecontrol system 400 can communicate with one or more remote entities,such as network services or human operators. According to some examples,the control system 400 stores vehicle control instructions 405, whichinclude radar control logic 403. In some implementations, otherinstructions can be stored for implementing other logical components asdescribed.

In operating the autonomous vehicle, the one or more processors 404 canaccess data from a road network data set 411 in order to determine aroute, immediate path forward, and information about a road segment thatis to be traversed by the vehicle. The road network data set 411 can bestored in the memory 406 of the vehicle and/or received responsivelyfrom an external source using one of the communication interfaces 418,438. For example, the memory 406 can store a database of roadwayinformation for future use, and the asynchronous communication interface438 can repeatedly receive data to update the database (e.g., afteranother vehicle does a run through a road segment).

According to some examples, one or more of the processors 404 executethe vehicle control instructions 405 to process sensor data 421 obtainedfrom the sensor interfaces 422, 428 for a road segment on which theautonomous vehicle is being driven. The one or more processors 404analyze the sensor data 421 to determine, for example, radar depthsettings 425 for radars 409 which are resident on the vehicle.

It is contemplated for embodiments described herein to extend toindividual elements and concepts described herein, independently ofother concepts, ideas or system, as well as for embodiments to includecombinations of elements recited anywhere in this application. Althoughembodiments are described in detail herein with reference to theaccompanying drawings, it is to be understood that the invention is notlimited to those precise embodiments. As such, many modifications andvariations will be apparent to practitioners skilled in this art.Accordingly, it is intended that the scope of the invention be definedby the following claims and their equivalents. Furthermore, it iscontemplated that a particular feature described either individually oras part of an embodiment can be combined with other individuallydescribed features, or parts of other embodiments, even if the otherfeatures and embodiments make no mentioned of the particular feature.Thus, the absence of describing combinations should not preclude theinventor from claiming rights to such combinations.

What is claimed is:
 1. A method for operating a vehicle, the methodcomprising: operating a set of radars on the vehicle, each radar in theset of radars including a depth setting which controls a correspondingrange of the radar from the vehicle; determining contextual informationabout a trip of the vehicle as the vehicle progresses over a roadsegment; and adjusting the corresponding range of at least one radar inthe set based on the contextual information.
 2. The method of claim 1,further comprising: making a selection of the at least one radar basedon the contextual information.
 3. The method of claim 1, wherein the atleast one radar is moved over an angular range that includes multipleviewing orientations, and wherein adjusting the corresponding range ofat least one radar includes selecting a viewing orientation from themultiple viewing orientations, and selecting the range of the radar atthe selected viewing orientation.
 4. The method of claim 3, whereinadjusting the corresponding range includes determining a duration inwhich the selected radar is actively signaling and monitoring when inthe selected viewing orientation.
 5. The method of claim 1, whereindetermining the contextual information includes determining informationabout a road segment that the vehicle is approaching.
 6. The method ofclaim 5, wherein the information about the road segment includesinformation that identifies at least one of (i) an intersection with atleast one other rod, (ii) a traffic light, (iii) road signage, or (iv) across walk.
 7. The method of claim 5, wherein the information about theroad segment includes information that identifies a likely point ofingress for other objects into a path of the vehicle on the roadsegment.
 8. The method of claim 5, wherein the information about theroad segment includes information that identifies a set of staticobjects which surround the road segment.
 9. The method of claim 5,wherein the contextual information includes one or more of a time ofday, a day of week or calendar day, or an amount of traffic.
 10. Themethod of claim 1, further comprising: autonomously controlling thevehicle based on information received from the set of radars.
 11. Themethod of claim 10, wherein each of (a) through (c) is repeated multipletimes as the vehicle completes the trip, and wherein the adjusting thecorresponding range includes selecting any one of the radars in the setfor adjustment in range.
 12. A control system for a vehicle, comprising:a set of processors; memory to store instructions; a plurality ofinterfaces for sensors of the vehicle, the plurality of interfacesincluding a set of radar interfaces; wherein the set of processorsexecute instructions that include: determine contextual informationabout a trip of the vehicle as the vehicle progresses over a roadsegment; and adjust the corresponding range of at least one radar in theset based on the contextual information.
 13. The control system of claim12, wherein the memory stores a map that identifies road segments,including a road segment which the vehicle is approaching, and whereinthe one or more processors determine the contextual information usingthe map.
 14. The control system of claim 13, wherein the one or moreprocessors identify, from the map, a set of static objects, and whereincontextual information includes information determined from the set ofstatic objects.
 15. A vehicle comprising: a control system; a set ofradars; a memory to store instructions and a map; one or more processorswhich execute the instructions to: access the map; determine contextualinformation from the map; and adjust a range of each radar in the set ofradars based on the determined contextual information.
 16. The vehicleof claim 15, wherein the one or more processors make a selection of theat least one radar based on the contextual information.
 17. The vehicleof claim 15, wherein the at least one radar is moved over an angularrange that includes multiple viewing orientations, and wherein the oneor more processors adjust the corresponding range of at least one radarby selecting a viewing orientation from the multiple viewingorientations, and by selecting the range of the radar at the selectedviewing orientation.
 18. The vehicle of claim 17, wherein the one ormore processors adjust the corresponding range by determining a durationin which the selected radar is actively signaling and monitoring when inthe selected viewing orientation.
 19. The vehicle of claim 15, whereinthe one or more processors determine the contextual information bydetermining information about a road segment that the vehicle isapproaching.
 20. The vehicle of claim 15, wherein the contextualinformation includes one or more of a time of day, a day of week orcalendar day, or an amount of traffic.